Companies & Industries

Hospitals Are Mining Patients' Credit Card Data to Predict Who Will Get Sick

Imagine getting a call from your doctor if you let your gym membership lapse, make a habit of buying candy bars at the checkout counter, or begin shopping at plus-size clothing stores. For patients of Carolinas HealthCare System, which operates the largest group of medical centers in North and South Carolina, such a day could be sooner than they think. Carolinas HealthCare, which runs more than 900 care centers, including hospitals, nursing homes, doctors’ offices, and surgical centers, has begun plugging consumer data on 2 million people into algorithms designed to identify high-risk patients so that doctors can intervene before they get sick. The company purchases the data from brokers who cull public records, store loyalty program transactions, and credit card purchases.

Information on consumer spending can provide a more complete picture than the glimpse doctors get during an office visit or through lab results, says Michael Dulin, chief clinical officer for analytics and outcomes research at Carolinas HealthCare. The Charlotte-based hospital chain is placing its data into predictive models that give risk scores to patients. Within two years, Dulin plans to regularly distribute those scores to doctors and nurses who can then reach out to high-risk patients and suggest changes before they fall ill. “What we are looking to find are people before they end up in trouble,” says Dulin, who is a practicing physician.

For a patient with asthma, the hospital would be able to assess how likely he is to arrive at the emergency room by looking at whether he’s refilled his asthma medication at the pharmacy, has been buying cigarettes at the grocery store, and lives in an area with a high pollen count, Dulin says. The system may also look at the probability of someone having a heart attack by considering factors such as the type of foods she buys and if she has a gym membership. “The idea is to use Big Data and predictive models to think about population health and drill down to the individual levels,” he says.

While Carolinas HealthCare can share patients’ risk assessments with their doctors under the hospital’s contract with its data provider, the health-care chain isn’t allowed to disclose details, such as specific transactions by an individual, says Dulin, who declined to name the data provider.

If the early steps are successful, though, Dulin says he’d like to renegotiate to get the data provider to share more specific details with the company’s doctors on their patients’ spending habits. “The data is already used to market to people to get them to do things that might not always be in the best interest of the consumer,” he says. “We are looking to apply this for something good.”

Many patients and their advocates are voicing concerns that Big Data’s expansion into medical care will threaten privacy. “It is one thing to have a number I can call if I have a problem or question; it is another thing to get unsolicited phone calls. I don’t like that,” says Jorjanne Murry, an accountant in Charlotte who has Type 1 diabetes and says she usually ignores calls from her health insurer trying to discuss her daily habits. “I think it is intrusive.”

Health advocates and privacy experts worry that relying more on data analysis also will erode doctor-patient relationships. “If the physician already has the information, the relationship changes from an exchange of information to a potential inquisition about behavior,” says Ryan Holmes, assistant director of health care ethics at the Markkula Center for Applied Ethics at Santa Clara University.

Data brokers have revealed few details on what they sell to health-care providers, and those acquiring the data are often barred from disclosing which company they purchased it from. Acxiom (ACXM) and LexisNexis (ENL) are two of the largest data brokers that collect information on individuals. Acxiom says its data are supposed to be used only for marketing, not for medical purposes or to be included in medical records. LexisNexis says it doesn’t sell consumer information to health insurers for the purpose of identifying patients at risk.

While some patients may benefit from data collection, hospitals also have a growing financial stake in knowing more about the people they care for. Under the Patient Protection and Affordable Care Act, known as Obamacare, hospital pay is becoming increasingly linked to quality metrics rather than the traditional fee-for-service model in which hospitals are paid based on the numbers of tests or procedures they perform. As a result, the U.S. has begun levying fines on hospitals that have too many patients readmitted within a month and rewarding hospitals that fare well against clinical benchmarks and on patient surveys.

University of Pittsburgh Medical Center, which operates more than 20 hospitals in Pennsylvania and a health insurance plan, is using demographic and household data to try to improve patients’ health as well as its bottom line. It says it doesn’t obtain details on individual credit card transactions, but more general data such as whether a patient owns her home, shops online, or lives with an elderly relative.

The UPMC Insurance Services Division, the health system’s insurance provider, bought data on more than 2 million of its members to make predictions about which individuals are most likely to use the emergency room or an urgent care center, says Pamela Peele, the system’s chief analytics officer.

Studies show that people with no children in the home who make less than $50,000 a year are more likely to use the ER rather than a private doctor, Peele says. UPMC wants to make sure those patients have access to a primary care physician or nurse practitioner they can contact before heading to the ER, she says. UPMC is also interested in knowing which patients don’t own a car, which could indicate they’ll have trouble getting routine, preventative care.

Being able to predict which patients are likely to get sick or end up at the ER has become particularly valuable for hospitals that also insure their patients, a relatively new practice that’s growing in popularity. UPMC, because it offers insurance, would be able to save money by keeping patients out of the ER.

Obamacare prevents insurers from denying coverage because of preexisting conditions or charging patients based on their health status, meaning the data can’t be used to raise rates or drop policies. “The traditional rating and underwriting has gone away with health-care reform,” says Robert Booz, an analyst at technology research and consulting firm Gartner (IT). “What they are trying to do is proactive care management, where we know you are a patient at risk for diabetes, so even before the symptoms show up we are going to try to intervene.”